Productionizing R scripts in the cloud

One of the greatest strength of R is the ease and speed of developing a prototype (let it be a report or dashboard, a statistical model or rule-based automation to solve a business problem etc), but deploying to production is not a broadly discussed topic — despite its importance. This hands-on talk focuses on best practices and actual R packages to help transforming the prototypes developed by eg a business analysts and data scientist into production jobs running in a secure environment that is easy to maintain — discussing the importance of logging, standardizing code style, source-code versioning, unit and integration tests, securing credentials, effective helper functions to connect to databases, open-source and SaaS job schedulers, dockerizing the run environment and scaling infrastructure.